How AI influences engineering students’ competencies development: a literature review

Purpose This paper aims to discuss how artificial intelligence (AI) fosters the competencies demanded by engineering students to work in the Industry 4.0 (I4.0) context. Design/methodology/approach A systematic literature review was conducted using the PRISMA method. The analysis encompassed 127 peer-reviewed articles (2022–2025), which were analysed to identify competencies, and their AI association. Findings The findings detail how engineering students’ competencies are developed based on AI use. Fourteen competencies are categorized as technical (i.e. automation, collaborativeness, programming, simulation), methodological (i.e. data analytics and modelling, problem-solving, analytical thinking, decision-making), social (i.e. teamwork) and personal (i.e. adaptability, communication, ethics, innovative behaviour, self-development learning). Practical implications This research can guide new educational methods that facilitate the development of students’ competencies applying AI, and guidelines on revising educational curricula affected by I4.0, which include support learning creation based on active learning to promote students as knowledge producers. Originality/value This paper provides a novel detailed synthesis of relevant competencies for engineering students and the AI contribution to competences development. The findings reply to research gaps on how AI supports technical and human-centred competencies for engineering students to act in the I4.0, which is underexplored in the current literature.